WO2021051541A1

WO2021051541A1 - Method and apparatus for achieving simultaneous gray release based on microservice framework, and computer device

Info

Publication number: WO2021051541A1
Application number: PCT/CN2019/117216
Authority: WO
Inventors: 伍春林; 杨定朝; 童志刚
Original assignee: 平安科技（深圳）有限公司
Priority date: 2019-09-18
Filing date: 2019-11-11
Publication date: 2021-03-25
Also published as: CN110753031B; CN110753031A

Abstract

A method and apparatus for achieving simultaneous gray release based on a microservice framework, a computer device, and a storage medium. The method comprises: receiving an invocation request directing to a target microservice; parsing the invocation request to obtain specified data; obtaining a simultaneous gray release strategy provided by a gray release strategy providing terminal; if the specified data does not fall within a preset range of the simultaneous gray release strategy, determining whether the current microservice belongs to the simultaneous gray release strategy; if the current microservice does not belong to the simultaneous gray release strategy, determining whether the target microservice belongs to the simultaneous gray release strategy; and if the target microservice belongs to the simultaneous gray release strategy, shunting the invocation request to a grayscale service instance of the target microservice, and establishing a signaling channel. Therefore, simultaneous gray release is achieved, and gray release efficiency is improved.

Description

Gray scale method, device and computer equipment based on microservice framework

This application claims the priority of a Chinese patent application filed with the Chinese Patent Office on September 18, 2019, the application number is 201910882733.5, and the invention title is "A gray-scale method, device and computer equipment based on a microservice framework", and its entire content Incorporated in this application by reference.

Technical field

This application relates to the computer field, in particular to a grayscale method, device, computer equipment and storage medium based on a microservice framework.

Background technique

Gray release refers to a release method in which there are different service versions within the same time period, and a smooth transition between the original version and the new version. At present, the main problems with gray-scale publishing are as follows: Generally, single-architecture services are used for gray-scale publishing. When gray-scale publishing requires multiple service instances, the cost is high and the efficiency is low; only a single service is supported for gray-scale publishing. Realize the gray release of multiple related services together; the service party must not only set the version of the service, but also set the gray release strategy. The process of setting the gray release is cumbersome and time-consuming. Therefore, the traditional gray-scale release technical solution is in urgent need of improvement.

technical problem

The main purpose of this application is to provide a grayscale method, device, computer equipment and storage medium based on a microservice framework, aiming to improve the efficiency of grayscale publishing.

Technical solutions

In order to achieve the above-mentioned purpose of the invention, this application proposes a gray-scale method based on a microservice framework, which includes the following steps:

Receive a call request directed to a target microservice, where the call request is generated by the current microservice of the user terminal, the current microservice and the target microservice do not belong to the same microservice cluster, and the current microservice refers to the current microservice A microservice that maintains a communication connection with the user terminal;

Parsing the call request to obtain designated data, where the designated data includes the ip address, request header, or request parameter of the user terminal;

Obtaining the gray-scale strategy provides a gray-scale strategy provided by the terminal, and the gray-scale strategy is a strategy that instructs at least two microservice clusters to perform gray-scale publishing;

Judging whether the specified data falls within the preset range of the one gray scale strategy;

If the specified data does not fall within the preset range of the integrated gray-scale strategy, use a preset gray-level strategy judgment method to determine whether the current microservice belongs to the integrated gray-scale strategy;

If the current microservice does not belong to the gray-scale integration strategy, determining whether the target microservice belongs to the gray-scale integration strategy;

If the target microservice belongs to the gray-scale policy, then the call request is diverted to the gray-scale service instance of the target microservice, and a signal connection channel is established, wherein one end of the signal connection channel is connected to the The other end of the user terminal is connected to gray-scale service instances of other micro-services in the same gray-scale strategy except for the target micro-service.

Beneficial effect

The grayscale method, device, computer equipment, and storage medium of this application based on the microservice framework receive a call request pointing to the target microservice; parse the call request to obtain the specified data; obtain the grayscale policy provided by the terminal Degree strategy; if the specified data does not fall within the preset range of the integrated gray-scale strategy, determine whether the current microservice belongs to the integrated gray-scale strategy; if the current microservice does not belong to the If the target microservice belongs to the gray-level strategy together, it is judged whether the target microservice belongs to the gray-level strategy together; if the target microservice belongs to the gray-level strategy together, the call request is diverted to the gray-level strategy of the target microservice. Service instance, and establish a signal connection channel, wherein one end of the signal connection channel is connected to the user terminal, and the other end is connected to the gray level of other microservices in the same gray level strategy except the target microservice. Degree service instance. So as to realize the gray-scale release together and improve the efficiency of gray-scale release.

Description of the drawings

FIG. 1 is a schematic flowchart of a grayscale method based on a microservice framework according to an embodiment of the application;

2 is a schematic block diagram of the structure of a grayscale device based on a microservice framework according to an embodiment of the application;

FIG. 3 is a schematic block diagram of the structure of a computer device according to an embodiment of the application.

The realization, functional characteristics, and advantages of the purpose of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings.

The best implementation of this application

In order to make the purpose, technical solutions, and advantages of this application clearer, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not used to limit the present application.

1, an embodiment of the present application provides a grayscale method based on a microservice framework, including the following steps:

S1. Receive a call request pointing to a target microservice, where the call request is generated by the current microservice of the user terminal, and the current microservice and the target microservice do not belong to the same microservice cluster, and the current microservice Refers to the microservice that currently maintains a communication connection with the user terminal;

S2. Parse the call request to obtain designated data, where the designated data includes the ip address, request header, or request parameter of the user terminal;

S3. Obtain a gray-scale strategy. Provide a gray-scale strategy provided by the terminal, where the gray-scale strategy is a strategy for instructing at least two microservice clusters to perform gray-scale publishing;

S4. Determine whether the specified data falls within the preset range of the one gray scale strategy;

S5. If the specified data does not fall within the preset range of the integrated gray-scale strategy, determine whether the current microservice belongs to the integrated gray-scale strategy through a preset gray-scale strategy judgment method;

S6. If the current microservice does not belong to the gray-level strategy, determine whether the target microservice belongs to the gray-scale strategy;

S7. If the target microservice belongs to the gray-scale strategy, the call request is diverted to the gray-scale service instance of the target microservice, and a signal connection channel is established, wherein one end of the signal connection channel is connected to The other end of the user terminal is connected to gray-scale service instances of other micro-services in the same gray-scale strategy except for the target micro-service.

As described in step S1 above, receiving a call request pointing to a target microservice, wherein the call request is generated by the current microservice of the user terminal, and the current microservice and the target microservice do not belong to the same microservice cluster, The current microservice refers to a microservice that currently maintains a communication connection with the user terminal. Wherein the call request is generated by the current microservice of the user terminal, it means that the call request is triggered by the user terminal when the current microservice is used, and is generated by the current microservice to point to the target microservice . That is, the target microservice has an association relationship with the current microservice, and belongs to a combination of microservices that can be published together in grayscale.

As described in step S2 above, the call request is parsed to obtain designated data, and the designated data includes the ip address, request header, or request parameter of the user terminal. Wherein, the request includes information such as the ip address, request header, or request parameters of the user terminal, so the specified data is obtained by parsing the request. For example, when the call request is encapsulated using the HTTP communication protocol, the format is, for example, a request line, a request header, a blank line, and the request content. Therefore, by calling the format of the passed protocol, the calling request is parsed to obtain the specified data. The specified data is, for example, a character string in a predetermined position in the request header. The specified data is used as a basis for subsequent grayscale release and distribution, that is, it is used to determine how the user terminal should distribute. The request parameter refers to the parameter in the request, and the value of the request parameter may be used as a basis for dividing the user terminal, so as to determine which version of the service the user terminal should be diverted to.

As described in step S3 above, obtaining a gray-scale strategy provides a gray-scale strategy provided by the terminal, and the gray-scale strategy is a strategy that instructs at least two microservice clusters to perform gray-scale publishing. The gray-level strategy is for example: judging whether the ip address of the user terminal falls within the preset address range, and if it falls within the preset address range, the user terminal is identified as a gray-level strategy user. The user terminal should implement a gray-scale strategy to release at least two microservice clusters in gray-scale. The gray-scale strategy adopted in this application comes from the gray-scale strategy provider terminal, so that the gray-scale strategy setting is separated from the gray-scale version mark. When the service provider performs the gray-scale release, only the version of the microservice is required. Just mark it, which overcomes the cumbersome and time-consuming defects of the traditional scheme setting gray-scale release process.

As described in step S4 above, it is determined whether the specified data falls within the preset range of the one gray scale strategy. The specific judgment method is, for example, calculating the similarity value between the designated data and the preset character string according to a preset similarity algorithm, and judging whether the similarity value is less than a preset similarity threshold; If the similarity value is not less than the preset similarity threshold, then obtain the first key corresponding to the first version gray user, the second version gray user,..., the nth version gray user agreed in the one gray policy Word, second keyword,..., nth keyword, wherein the one grayscale strategy pre-appoints n versions of grayscale users; it is determined whether the specified data records the first keyword, second keyword, ...Or the nth keyword; if the designated data records the first keyword, the second keyword, ... or the nth keyword, it is determined that the designated data falls within the preset range of the same gray scale strategy And mark the user terminal as a version gray user corresponding to the first keyword, the second keyword, ... or the nth keyword. Thus, it is possible to further carry out the gray release of multi-service and multi-version.

As described in the above step S5, if the specified data does not fall within the preset range of the gray-scale strategy, the preset gray-scale strategy judgment method is used to determine whether the current microservice belongs to the common gray-scale strategy. Grayscale strategy. The preset gray-scale strategy judgment method is, for example: if the specified data does not fall within the preset range of the gray-scale strategy, obtain the version number of the current microservice; obtain the gray-scale The version number of the microservice in the policy; determine whether the version number of the current microservice is the same as the version number of the microservice in the integrated grayscale policy; if the version number of the current microservice is the same as the integrated grayscale If the version numbers of the microservices in the policies are the same, it is determined that the current microservices belong to the same gray-scale policy.

As described in the above step S6, if the current microservice does not belong to the gray-level integration strategy, it is determined whether the target microservice belongs to the gray-level integration strategy. The method used to determine whether the target microservice belongs to the gray-scale strategy can use the aforementioned gray-scale strategy judgment method, or any other method, such as judging the list of microservices recorded in the gray-scale strategy. Whether the microservice name of the target microservice is included in the.

As described in step S7 above, if the target microservice belongs to the grayscale policy, then the call request is diverted to the grayscale service instance of the target microservice, and a signal connection channel is established, wherein the signal One end of the connection channel is connected to the user terminal, and the other end is connected to gray-scale service instances of other micro-services in the same gray-scale strategy except for the target micro-service. If the target microservice belongs to the gray-level strategy, it indicates that the target microservice and the microservice cluster in which the target microservice is located should perform a gray-scale operation, so the call request is diverted to all The gray-scale service instance of the target microservice, and the gray-scale publication of the microservice cluster where the target microservice is located, that is, a signal connection channel is established, wherein one end of the signal connection channel is connected to the user terminal, and the other end Connect to the gray-scale service instances of other micro-services in the same gray-scale strategy except for the target micro-service. Furthermore, it also includes: constructing a connection channel to enable the microservice cluster where the current microservice is located to perform grayscale publishing. In this way, multiple services (multiple microservice clusters, for example, including the microservice cluster specified in the same grayscale policy) can be published together in grayscale.

In one embodiment, the designated data is a character string recorded in a pre-appointed position in the request header, the gray scale strategy defines a plurality of preset ranges, and the determination of whether the designated data falls into the gray scale Step S4 within the preset range of the degree strategy includes:

S401: Calculate the similarity value between the designated data and the preset character string according to a preset similarity algorithm, and determine whether the similarity value is less than a preset similarity threshold;

S402. If the similarity value is not less than the preset similarity threshold, obtain the first version grayscale user, the second version grayscale user,..., the nth version grayscale user correspondence agreed in the one grayscale strategy The first keyword, the second keyword, ..., the nth keyword of, wherein the one grayscale strategy pre-appoints n versions of grayscale users;

S404: Determine whether the designated data records a first keyword, a second keyword, ... or an nth keyword;

S405. If the specified data records the first keyword, the second keyword, ... or the nth keyword, determine that the specified data falls within the preset range of the one gray scale strategy, and set all The user terminal is recorded as a version gray user corresponding to the first keyword, the second keyword, ... or the nth keyword.

As described above, it is possible to determine whether the specified data falls within the preset range of the gray-scale strategy. The preset similarity algorithm can be any algorithm, as long as the similarity value between the specified data and the preset character string can be calculated, such as a distance formula based on the law of cosine, a similarity algorithm based on a word frequency vector, and the like. If the similarity value is not less than the preset similarity threshold, it means that the corresponding designated data is similar to the preset character string, and therefore the corresponding user terminal is a gray-scale user. In addition, this application uses multiple versions of grayscale, so it is also necessary to determine which version of the grayscale user the user terminal is. Therefore, this application determines whether the designated data contains the first keyword, the second keyword, ... or the nth keyword, so as to record the user terminal as being related to the first keyword and the second keyword. The version gray user corresponding to the word, ... or the nth keyword. Accordingly, the accurate release of multi-version grayscale based on the microservice framework is realized. Wherein, the designated data is a character string recorded in a predetermined position in the request header, for example, a character string recorded before two special symbols (such as ?) in the request header.

In one embodiment, the step S401 of calculating a similarity value between the designated data and a preset character string according to a preset similarity algorithm, and determining whether the similarity value is less than a preset similarity threshold, includes :

S4011, adopt the formula:

Calculate the similarity value between the specified data and the preset character string, where similarity is the similarity value, A is the character frequency vector of the specified data, B is the character frequency vector of the preset character string, and Ai is the character frequency vector of the specified data. The number of occurrences of the i-th character of the designated data, and Bi is the number of occurrences of the i-th character of the preset character string;

S4012, according to the corresponding relationship between the character string and the similarity threshold, obtain a designated similarity threshold corresponding to the preset character string;

S4013: Determine whether the similarity value is less than the specified similarity threshold.

As described above, it is realized that the similarity value between the designated data and the preset character string is calculated according to the preset similarity algorithm, and it is determined whether the similarity value is less than the preset similarity threshold. The character frequency vector is a high-dimensional vector composed of the number of times (frequency) of each character in the character string as the high-dimensional value of the vector. That is, A=(A1,A2,...,An), where An is the frequency (number of occurrences) of the last character (a total of n characters). The similarity algorithm is calculated according to the cosine similarity between the designated data and the preset character string, so as to reflect the degree of similarity between the designated data and the preset character string. When the value of similarity is closer to 1, the more similar it is; the closer to 0, the more dissimilar it is.

In one embodiment, the step S4 of judging whether the specified data falls within the preset range of the one gray scale strategy includes:

S411. According to a preset encoding method, encode the ip address, request header, and request parameters of the user terminal into a matrix [B1, B2, B3], where B1 is the mapping value corresponding to the ip address, and B2 is the The mapping value corresponding to the request header, and B3 is the mapping value corresponding to the request parameter;

S412: Acquire a designated parameter matrix [C1, C2, C3] corresponding to the one gray-scale strategy according to the preset corresponding relationship between the gray-scale strategy and the parameter matrix;

S413. Through the formula: M=||[B1,B2,B3] ^T [C1,C2,C3]||, the division reference index M is obtained by calculation;

S414: Determine whether the reference index M falls within multiple preset numerical ranges;

S415. If the reference index M falls within a plurality of preset numerical ranges, determine that the specified data falls within the preset range of the same gray scale strategy, and divide the user terminal into Am , Where Am refers to a grayscale user of the mth version, and the grayscale user of the mth version corresponds to the numerical range in which the reference index M falls.

As described above, it is possible to determine whether the specified data falls within the preset range of the one gray scale strategy, and divide the user terminal into Am. Traditional gray-scale publishing solutions use a single factor for low-dimensional gray-scale publishing, while this application uses high-dimensional mixed grayscale, which is faster and more precise than the single-dimensional gray-scale solution of the traditional technology. Specifically, according to a preset coding method, the ip address, request header, and request parameters of the user terminal are coded into a matrix [B1, B2, B3]; according to the corresponding relationship between the preset gray level strategy and the parameter matrix, obtain The specified parameter matrix [C1, C2, C3] corresponding to the gray strategy provided by the gray strategy providing terminal; through the formula: M=||[B1,B2,B3] ^T [C1,C2,C3]|| , Calculate the division reference index M; then divide the gray users according to the reference index M. The encoding method is a method of sequentially mapping the ip address, request header, and request parameters of the user terminal to specific values, and then combining them to obtain a matrix. Therefore, this application can simultaneously integrate the ip address, request header, and request parameters of the user terminal to perform high-dimensional and accurate gray-scale release, and the division is faster and more accurate.

In one embodiment, after the step S4 of determining whether the designated data falls within the preset range of the one gray scale strategy, the method includes:

S41. If the specified data falls within the preset range of the one gray-scale strategy, offload the call request to the gray-scale service instance of the target microservice;

S42. Establish a communication channel. One end of the communication channel is connected to the user terminal, and the other end is connected to gray-scale service instances of other micro-services in the integrated gray-scale strategy except for the target micro-service.

As described above, the implementation of a gray-scale strategy is achieved. If the specified data falls within the preset range of the gray-level strategy, it indicates that the user terminal needs to implement the gray-scale strategy together (and the target microservice is also in the gray-scale strategy together), and the target Microservices should also be published in grayscale. Accordingly, the call request is diverted to the gray-scale service instance of the target microservice, so as to realize the gray-scale release of the target microservice. And a communication channel is established. One end of the communication channel is connected to the user terminal, and the other end is connected to the gray-scale service instances of other micro-services in the gray-scale policy together except for the target micro-service, so as to realize the integration Grayscale release. Further, it also includes: establishing a communication channel to enable the microservice cluster where the current microservice is located to perform grayscale publishing (this is because the current microservice and the target microservice have an association relationship and can be grayscale published together).

In one embodiment, the microservice has a version number, and if the specified data does not fall within the preset range of the gray-level strategy, the current gray-scale strategy determination method is used to determine the current Whether the microservice belongs to the step S5 of the gray-scale strategy includes:

S501: If the specified data does not fall within the preset range of the gray-scale strategy, obtain the version number of the current microservice;

S502. Obtain the version number of the microservice in the gray-scale strategy.

S503: Determine whether the version number of the current microservice is the same as the version number of the microservice in the one-level strategy;

S504: If the version number of the current microservice is the same as the version number of the microservice in the integrated grayscale strategy, determine that the current microservice belongs to the integrated grayscale strategy.

As described above, it is possible to determine whether the current microservice belongs to the gray scale strategy. This application adopts the microservice architecture, and the microservices have the form of version numbers, so that it is possible to publish multiple services and multiple versions at the same time grayscale release, and use the characteristics of microservices to reduce the grayscale release of multiple services and multiple versions at the same time cost. If the specified data does not fall within the preset range of the gray-scale strategy, it indicates that the request itself does not bring a gray-scale signal. Therefore, by judging whether the version number of the current microservice is the same as the version number of the microservice in the integration strategy, to determine whether the current microservice belongs to the integration strategy, and to further determine the current microservice Which version of the grayscale release of the service belongs to the one grayscale strategy.

In one embodiment, after the step S6 of determining whether the target microservice belongs to the gray-level policy, if the current microservice does not belong to the gray-level policy, the method includes:

S61. If the target microservice does not belong to the gray-level strategy, input the user terminal to the already-trained gray-level reclassification model based on the machine learning model for calculation, thereby obtaining the gray-level reclassification model The output result of, wherein the output result includes gray-scale users and non-gray-scale users;

S62. If the output result is a gray-scale user, offload the call request to the gray-scale service instance of the target microservice;

S63. If the output result is a non-grayscale user, then branch the call request to the non-grayscale service instance of the target microservice.

As mentioned above, the re-classification using the gray-level re-classification model is realized to further ensure the accuracy of gray-level publishing. Compared with the traditional technology, this application uses the already-trained gray-scale reclassification model based on the machine learning model to re-classify the user terminal, avoiding the inaccuracy of manually setting the gray-scale publishing, and thus can more accurately Perform gray-scale release, and then make the data information obtained by gray-scale release feedback more effective, and improve the success rate of gray-scale release. The machine learning model may be any model, for example, a CHAID decision tree model. The CHAID decision tree model refers to a decision tree model that uses the chi-square automatic interactive detection method CHAID. Here is a brief introduction to the principles of the CHAID decision tree: 1. Combine the group values that have no significant difference in the impact of the decision variables in the group; 2. Select the variable with the largest chi-square value as the tree classification variable; 3. Repeat the steps 1 and 2 until it fails Choose that the chi-square value is greater than a certain value or the P value is no longer less than a certain critical value, or the sample is less than a certain number. Among them, the modeling standard parameters of the decision tree are for example: the maximum number of layers of the decision tree is 4-5, the significance level of the parent node can be subdivided is 0.05, the minimum number of samples contained in the parent node is 150, and the minimum sample contained in the child nodes The number is 50.

Referring to FIG. 2, an embodiment of the present application provides a grayscale device based on a microservice framework, including:

The call request receiving unit 10 is configured to receive a call request directed to a target microservice, wherein the call request is generated by the current microservice of the user terminal, and the current microservice and the target microservice do not belong to the same microservice cluster , The current microservice refers to a microservice that currently maintains a communication connection with the user terminal;

The designated data obtaining unit 20 is configured to parse the call request to obtain designated data, and the designated data includes the ip address, request header, or request parameter of the user terminal;

A gray-level strategy obtaining unit 30 is configured to obtain a gray-scale strategy provided by the terminal to provide a gray-scale strategy together, where the gray-scale strategy is a strategy that instructs at least two microservice clusters to perform grayscale publishing;

The preset range determining unit 40 is configured to determine whether the specified data falls within the preset range of the one gray scale strategy;

The gray-scale strategy judging unit 50 is configured to determine whether the current microservice belongs to all the micro-services through a preset gray-scale strategy judgment method if the specified data does not fall within the preset range of the gray-scale strategy. Describe a gray-scale strategy;

The target microservice determining unit 60 is configured to determine whether the target microservice belongs to the grayscale policy if the current microservice does not belong to the grayscale policy;

The signal connection channel establishment unit 70 is configured to, if the target microservice belongs to the gray-scale policy, then divert the call request to the gray-scale service instance of the target microservice, and establish a signal connection channel, wherein One end of the signal connection channel is connected to the user terminal, and the other end is connected to gray-scale service instances of other micro-services in the same gray-scale strategy except for the target micro-service.

The operations performed by the above-mentioned units respectively correspond to the steps of the grayscale method based on the microservice framework of the foregoing embodiment one by one, and will not be repeated here.

In one embodiment, the specified data is a character string recorded in a pre-appointed position in the request header, the one gray scale strategy defines a plurality of preset ranges, and the preset range determining unit 40 includes:

The similarity calculation subunit is configured to calculate the similarity value between the designated data and the preset character string according to a preset similarity algorithm, and determine whether the similarity value is less than a preset similarity threshold;

The keyword acquisition subunit is used to acquire the first version grayscale user, the second version grayscale user,..., the first version specified in the one grayscale strategy if the similarity value is not less than the preset similarity threshold value. The first keyword, the second keyword, ..., the nth keyword corresponding to the n-version gray-scale user, wherein the one gray-scale strategy pre-appoints n-version gray-scale users;

The keyword judgment subunit is used to judge whether the specified data records the first keyword, the second keyword, ... or the nth keyword;

The gray scale mark division subunit is used to determine that the specified data falls into the pre-defined gray scale strategy if the specified data contains the first keyword, the second keyword, ... or the nth keyword. Set within the range, and record the user terminal as a version gray user corresponding to the first keyword, the second keyword, ... or the nth keyword.

The operations performed by the above-mentioned sub-units respectively correspond to the steps of the gray-scale method based on the microservice framework of the foregoing embodiment one-to-one, and will not be repeated here.

In one embodiment, the similarity calculation subunit includes:

Similarity calculation module, used to adopt formula:

A designated similarity threshold acquisition module, configured to acquire a designated similarity threshold corresponding to the preset character string according to the corresponding relationship between the character string and the similarity threshold;

The designated similarity threshold judgment module is used to judge whether the similarity value is less than the designated similarity threshold.

The operations performed by the above-mentioned modules respectively correspond to the steps of the gray-scale method based on the microservice framework of the foregoing embodiment one by one, and will not be repeated here.

In one embodiment, the preset range determining unit 40 includes:

The encoding subunit is used to encode the ip address, request header, and request parameters of the user terminal into a matrix [B1, B2, B3] according to a preset encoding method, where B1 is the mapping value corresponding to the ip address, B2 is the mapping value corresponding to the request header, and B3 is the mapping value corresponding to the request parameter;

The designated parameter matrix acquiring subunit is used to acquire the designated parameter matrix [C1, C2, C3] corresponding to the one gray strategy according to the corresponding relationship between the preset gray strategy and the parameter matrix;

The division reference index M is used to obtain the subunit, which is used to calculate the division reference index M through the formula: M=||[B1,B2,B3] ^T [C1,C2,C3]||;

A numerical value range judging subunit for judging whether the reference index M falls within a plurality of preset numerical ranges;

The user terminal divides sub-units for determining that the specified data falls within the preset range of the same gray scale strategy if the reference index M falls within a plurality of preset numerical ranges, and sets all The user terminal is divided into Am, where Am refers to an m-th version of gray-scale user, and the m-th version of gray-scale user corresponds to the numerical range in which the reference index M falls.

In one embodiment, the device includes:

A call request shunting unit, configured to shunt the call request to the gray service instance of the target microservice if the specified data falls within the preset range of the gray-level strategy;

The communication channel establishment unit is configured to establish a communication channel, one end of the communication channel is connected to the user terminal, and the other end is connected to the gray level of other microservices in the same gray level strategy except the target microservice Service instance.

In one embodiment, the microservice has a version number, and the gray-scale strategy judgment unit 50 includes:

The current microservice version number obtaining subunit is configured to obtain the version number of the current microservice if the specified data does not fall within the preset range of the gray-scale strategy;

The gray-scale strategy version number obtaining subunit is used to obtain the version number of the microservice in the gray-scale strategy;

The version number judging subunit is used to judge whether the version number of the current microservice is the same as the version number of the microservice in the same gray-scale strategy;

A gray-scale policy determination subunit is configured to determine that the current micro-service belongs to the gray-scale policy if the version number of the current microservice is the same as the version number of the micro-service in the gray-scale policy.

In one embodiment, the device includes:

The output result obtaining unit is configured to, if the target microservice does not belong to the gray-level strategy, input the user terminal into the already-trained gray-level reclassification model based on the machine learning model for calculation, thereby obtaining the The output result of the gray-scale reclassification model, where the output result includes gray-scale users and non-gray-scale users;

A gray-scale service instance offloading unit, configured to offload the call request to the gray-scale service instance of the target microservice if the output result is a gray-scale user;

The non-gray-scale service instance distribution unit is configured to distribute the call request to the non-gray-scale service instance of the target microservice if the output result is a non-gray-scale user.

3, an embodiment of the present application also provides a computer device. The computer device may be a server, and its internal structure may be as shown in the figure. The computer equipment includes a processor, a memory, a network interface, and a database connected through a system bus. Among them, the processor designed by the computer is used to provide calculation and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database of the computer equipment is used to store the data used in the grayscale method based on the microservice framework. The network interface of the computer device is used to communicate with an external terminal through a network connection. The computer program is executed by the processor to realize a gray-scale method based on the microservice framework.

The above-mentioned processor executes the above-mentioned grayscale method based on the microservice framework, wherein the steps included in the method respectively correspond to the steps of executing the grayscale method based on the microservice framework of the foregoing embodiment one-to-one, and will not be repeated here.

Those skilled in the art can understand that the structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied.

An embodiment of the present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, a grayscale method based on a microservice framework is implemented, wherein the steps included in the method are respectively the same as those in the execution. The steps of the gray-scale method based on the microservice framework in the foregoing embodiment correspond one-to-one, and will not be repeated here. The computer-readable storage medium is, for example, a non-volatile computer-readable storage medium, or a volatile computer-readable storage medium.

Claims

A gray-scale method based on a microservice framework, which is characterized in that it includes:

Receive a call request directed to a target microservice, where the call request is generated by the current microservice of the user terminal, the current microservice and the target microservice do not belong to the same microservice cluster, and the current microservice refers to the current microservice A microservice that maintains a communication connection with the user terminal;

Parsing the call request to obtain designated data, where the designated data includes the ip address, request header, or request parameter of the user terminal;

Obtaining the gray-scale strategy provides a gray-scale strategy provided by the terminal, and the gray-scale strategy is a strategy that instructs at least two microservice clusters to perform gray-scale publishing;

Judging whether the specified data falls within the preset range of the one gray scale strategy;

If the specified data does not fall within the preset range of the integrated gray-scale strategy, use a preset gray-level strategy judgment method to determine whether the current microservice belongs to the integrated gray-scale strategy;

If the current microservice does not belong to the gray-scale integration strategy, determining whether the target microservice belongs to the gray-scale integration strategy;

If the target microservice belongs to the gray-scale policy, then the call request is diverted to the gray-scale service instance of the target microservice, and a signal connection channel is established, wherein one end of the signal connection channel is connected to the The other end of the user terminal is connected to gray-scale service instances of other micro-services in the same gray-scale strategy except for the target micro-service.
The grayscale integration method based on the microservice framework according to claim 1, wherein the specified data is a character string recorded in a pre-appointed position in the request header, and the grayscale integration strategy defines a plurality of preset ranges , The step of judging whether the designated data falls within the preset range of the one gray scale strategy includes:

According to a preset similarity algorithm, calculate a similarity value between the designated data and a preset character string, and determine whether the similarity value is less than a preset similarity threshold;

If the similarity value is not less than the preset similarity threshold, then obtain the first version gray user, the second version gray user,..., the first version gray user corresponding to the nth version gray user agreed in the one gray policy. A keyword, a second keyword, ..., an nth keyword, in which the one grayscale strategy pre-appoints n versions of grayscale users;

Determine whether the designated data records the first keyword, the second keyword, ... or the nth keyword;

If the specified data records the first keyword, the second keyword, ... or the nth keyword, it is determined that the specified data falls within the preset range of the gray-scale strategy, and the user The terminal is recorded as a version gray user corresponding to the first keyword, the second keyword, ... or the nth keyword.
The grayscale method based on the microservice framework according to claim 2, wherein the similarity value between the designated data and the preset character string is calculated according to a preset similarity algorithm, and the The steps of whether the similarity value is less than the preset similarity threshold include:

Use the formula:

Calculate the similarity value between the specified data and the preset character string, where similarity is the similarity value, A is the character frequency vector of the specified data, B is the character frequency vector of the preset character string, and Ai is the character frequency vector of the specified data. The number of occurrences of the i-th character of the designated data, and Bi is the number of occurrences of the i-th character of the preset character string;

Obtaining the designated similarity threshold corresponding to the preset character string according to the correspondence between the character string and the similarity threshold;

It is determined whether the similarity value is less than the specified similarity threshold.
The grayscale integration method based on the microservice framework of claim 1, wherein the step of judging whether the specified data falls within the preset range of the grayscale integration strategy comprises:

According to a preset encoding method, encode the ip address, request header, and request parameters of the user terminal into a matrix [B1, B2, B3], where B1 is the mapping value corresponding to the ip address, and B2 is the request header The corresponding mapping value, B3 is the mapping value corresponding to the request parameter;

According to the preset corresponding relationship between the gray level strategy and the parameter matrix, obtain the designated parameter matrix [C1, C2, C3] corresponding to the one gray level strategy;

Through the formula: M=||[B1,B2,B3] T [C1,C2,C3]||, the division reference index M is calculated;

Judging whether the reference index M falls within a plurality of preset numerical ranges;

If the reference index M falls within a plurality of preset numerical ranges, it is determined that the specified data falls within the preset range of the one gray scale strategy, and the user terminal is divided into Am, where Am refers to a grayscale user of the mth version, and the grayscale user of the mth version corresponds to the numerical range in which the reference index M falls.
The grayscale method based on the microservice framework according to claim 1, wherein after the step of determining whether the specified data falls within the preset range of the grayscale strategy, the method comprises:

If the specified data falls within the preset range of the one gray-scale strategy, diverting the call request to the gray-scale service instance of the target microservice;

A communication channel is established, one end of the communication channel is connected to the user terminal, and the other end is connected to a gray-scale service instance of other micro-services in the same gray-scale strategy except for the target micro-service.
The grayscale integration method based on the microservice framework according to claim 1, wherein the microservice has a version number, and if the specified data does not fall within the preset range of the grayscale integration strategy, Then, the step of judging whether the current microservice belongs to the same gray-scale strategy through a preset gray-scale strategy judgment method includes:

If the specified data does not fall within the preset range of the one gray-scale strategy, obtain the version number of the current microservice;

Obtain the version number of the microservice in the one gray-scale strategy;

Judging whether the version number of the current microservice is the same as the version number of the microservice in the same gray-scale strategy;

If the version number of the current microservice is the same as the version number of the microservice in the integrated grayscale strategy, it is determined that the current microservice belongs to the integrated grayscale strategy.
The gray-scale integration method based on the microservice framework according to claim 1, wherein if the current micro-service does not belong to the gray-scale integration strategy, then it is determined whether the target microservice belongs to the gray-scale integration strategy. After the steps of the grayscale strategy, include:

If the target microservice does not belong to the gray-level strategy, the user terminal is input to the already-trained gray-level reclassification model based on the machine learning model for operation, so as to obtain the output of the gray-level reclassification model As a result, the output result includes gray-scale users and non-gray-scale users;

If the output result is a gray-scale user, diverting the call request to the gray-scale service instance of the target microservice;

If the output result is a non-grayscale user, the call request is diverted to the non-grayscale service instance of the target microservice.
A gray-scale device based on a microservice framework, which is characterized in that it includes:

A call request receiving unit for receiving a call request directed to a target microservice, wherein the call request is generated by the current microservice of the user terminal, and the current microservice and the target microservice do not belong to the same microservice cluster, The current microservice refers to a microservice that currently maintains a communication connection with the user terminal;

A designated data acquisition unit, configured to parse the call request to obtain designated data, the designated data including the ip address, request header, or request parameter of the user terminal;

A gray-level strategy acquisition unit for acquiring a gray-scale strategy to provide a gray-scale strategy provided by the terminal, and the gray-scale strategy is a strategy that instructs at least two microservice clusters to perform gray-scale publishing;

A preset range judging unit, configured to judge whether the specified data falls within the preset range of the one gray scale strategy;

The gray-scale strategy judgment unit is configured to determine whether the current microservice belongs to the preset gray-scale strategy judgment method if the specified data does not fall within the preset range of the gray-scale strategy. Together gray strategy;

A target microservice judging unit, configured to determine whether the target microservice belongs to the grayscale policy if the current microservice does not belong to the grayscale policy;

The signal connection channel establishment unit is configured to, if the target microservice belongs to the gray-scale policy, offload the call request to the gray-scale service instance of the target microservice, and establish a signal connection channel, wherein One end of the signal connection channel is connected to the user terminal, and the other end is connected to the gray-scale service instance of other micro-services in the same gray-scale strategy except for the target micro-service.
The micro-service framework-based grayscale device according to claim 8, wherein the specified data is a character string recorded in a pre-appointed position in the request header, and the grayscale strategy defines a plurality of preset ranges , The preset range determining unit 40 includes:

The similarity calculation subunit is configured to calculate the similarity value between the designated data and the preset character string according to a preset similarity algorithm, and determine whether the similarity value is less than a preset similarity threshold;

The keyword acquisition subunit is used to acquire the first version grayscale user, the second version grayscale user,..., the first version specified in the one grayscale strategy if the similarity value is not less than the preset similarity threshold value. The first keyword, the second keyword, ..., the nth keyword corresponding to the n-version gray-scale user, wherein the one gray-scale strategy pre-appoints n-version gray-scale users;

The keyword judgment subunit is used to judge whether the specified data records the first keyword, the second keyword, ... or the nth keyword;

The gray scale mark division subunit is used to determine that the specified data falls into the pre-defined gray scale strategy if the specified data contains the first keyword, the second keyword, ... or the nth keyword. Set within the range, and record the user terminal as a version gray user corresponding to the first keyword, the second keyword, ... or the nth keyword.
The grayscale device based on the microservice framework according to claim 9, wherein the similarity calculation subunit comprises:

Similarity calculation module, used to adopt formula:

Calculate the similarity value between the specified data and the preset character string, where similarity is the similarity value, A is the character frequency vector of the specified data, B is the character frequency vector of the preset character string, and Ai is the character frequency vector of the specified data. The number of occurrences of the i-th character of the designated data, and Bi is the number of occurrences of the i-th character of the preset character string;

A designated similarity threshold acquisition module, configured to acquire a designated similarity threshold corresponding to the preset character string according to the corresponding relationship between the character string and the similarity threshold;

The designated similarity threshold judgment module is used to judge whether the similarity value is less than the designated similarity threshold.
The grayscale device based on the microservice framework according to claim 8, wherein the preset range determining unit 40 comprises:

The encoding subunit is used to encode the ip address, request header, and request parameters of the user terminal into a matrix [B1, B2, B3] according to a preset encoding method, where B1 is the mapping value corresponding to the ip address, B2 is the mapping value corresponding to the request header, and B3 is the mapping value corresponding to the request parameter;

The designated parameter matrix acquiring subunit is used to acquire the designated parameter matrix [C1, C2, C3] corresponding to the one gray strategy according to the corresponding relationship between the preset gray strategy and the parameter matrix;

The division reference index M is used to obtain the subunit, which is used to calculate the division reference index M through the formula: M=||[B1,B2,B3] T [C1,C2,C3]||;

A numerical value range judging subunit for judging whether the reference index M falls within a plurality of preset numerical ranges;

The user terminal divides sub-units for determining that the specified data falls within the preset range of the same gray scale strategy if the reference index M falls within a plurality of preset numerical ranges, and sets all The user terminal is divided into Am, where Am refers to an m-th version of gray-scale user, and the m-th version of gray-scale user corresponds to the numerical range in which the reference index M falls.
The grayscale device based on the microservice framework of claim 8, wherein the device comprises:

A call request shunting unit, configured to shunt the call request to the gray service instance of the target microservice if the specified data falls within the preset range of the gray-level strategy;

The communication channel establishment unit is configured to establish a communication channel, one end of the communication channel is connected to the user terminal, and the other end is connected to the gray level of other microservices in the same gray level strategy except the target microservice Service instance.
The grayscale device based on the microservice framework according to claim 8, wherein the microservice has a version number, and the grayscale strategy judgment unit 50 includes:

The current microservice version number obtaining subunit is configured to obtain the version number of the current microservice if the specified data does not fall within the preset range of the gray-scale strategy;

The gray-scale strategy version number obtaining subunit is used to obtain the version number of the microservice in the gray-scale strategy;

The version number judging subunit is used to judge whether the version number of the current microservice is the same as the version number of the microservice in the same gray-scale strategy;

A gray-scale policy determination subunit is configured to determine that the current micro-service belongs to the gray-scale policy if the version number of the current microservice is the same as the version number of the micro-service in the gray-scale policy.
The grayscale device based on the microservice framework of claim 8, wherein the device comprises:

The output result obtaining unit is configured to, if the target microservice does not belong to the gray-level strategy, input the user terminal into the already-trained gray-level reclassification model based on the machine learning model for calculation, thereby obtaining the The output result of the gray-scale reclassification model, where the output result includes gray-scale users and non-gray-scale users;

A gray-scale service instance offloading unit, configured to offload the call request to the gray-scale service instance of the target microservice if the output result is a gray-scale user;

The non-gray-scale service instance distribution unit is configured to distribute the call request to the non-gray-scale service instance of the target microservice if the output result is a non-gray-scale user.
A computer device includes a memory and a processor, the memory stores a computer program, and is characterized in that, when the processor executes the computer program, a grayscale method based on a microservice framework is implemented, and the microservice framework is based on a grayscale method. The gray-scale methods include:

Receive a call request directed to a target microservice, where the call request is generated by the current microservice of the user terminal, the current microservice and the target microservice do not belong to the same microservice cluster, and the current microservice refers to the current microservice A microservice that maintains a communication connection with the user terminal;

Parsing the call request to obtain designated data, where the designated data includes the ip address, request header, or request parameter of the user terminal;

Obtaining the gray-scale strategy provides a gray-scale strategy provided by the terminal, and the gray-scale strategy is a strategy that instructs at least two microservice clusters to perform gray-scale publishing;

Judging whether the specified data falls within the preset range of the one gray scale strategy;

If the specified data does not fall within the preset range of the integrated gray-scale strategy, use a preset gray-level strategy judgment method to determine whether the current microservice belongs to the integrated gray-scale strategy;

If the current microservice does not belong to the gray-scale integration strategy, determining whether the target microservice belongs to the gray-scale integration strategy;

If the target microservice belongs to the gray-scale policy, then the call request is diverted to the gray-scale service instance of the target microservice, and a signal connection channel is established, wherein one end of the signal connection channel is connected to the The other end of the user terminal is connected to gray-scale service instances of other micro-services in the same gray-scale strategy except for the target micro-service.
The computer device according to claim 15, wherein the specified data is a character string recorded in a pre-appointed position in the request header, the one gray scale strategy defines a plurality of preset ranges, and the judgment of the specified The steps of whether the data falls within the preset range of the one gray-scale strategy include:

According to a preset similarity algorithm, calculate a similarity value between the designated data and a preset character string, and determine whether the similarity value is less than a preset similarity threshold;

If the similarity value is not less than the preset similarity threshold, then obtain the first version gray user, the second version gray user,..., the first version gray user corresponding to the nth version gray user agreed in the one gray policy. A keyword, a second keyword, ..., an nth keyword, in which the one grayscale strategy pre-appoints n versions of grayscale users;

Determine whether the designated data records the first keyword, the second keyword, ... or the nth keyword;

If the specified data records the first keyword, the second keyword, ... or the nth keyword, it is determined that the specified data falls within the preset range of the gray-scale strategy, and the user The terminal is recorded as a version gray user corresponding to the first keyword, the second keyword, ... or the nth keyword.
The computer device according to claim 16, wherein the similarity value between the designated data and a preset character string is calculated according to a preset similarity algorithm, and it is determined whether the similarity value is less than a preset The steps of similarity threshold include:

Use the formula:

Calculate the similarity value between the specified data and the preset character string, where similarity is the similarity value, A is the character frequency vector of the specified data, B is the character frequency vector of the preset character string, and Ai is the character frequency vector of the specified data. The number of occurrences of the i-th character of the designated data, and Bi is the number of occurrences of the i-th character of the preset character string;

Obtaining the designated similarity threshold corresponding to the preset character string according to the correspondence between the character string and the similarity threshold;

It is determined whether the similarity value is less than the specified similarity threshold.
A computer-readable storage medium having a computer program stored thereon, wherein the computer program implements a grayscale method based on a microservice framework when the computer program is executed by a processor, the grayscale method based on a microservice framework ,include:

Receive a call request directed to a target microservice, where the call request is generated by the current microservice of the user terminal, the current microservice and the target microservice do not belong to the same microservice cluster, and the current microservice refers to the current microservice A microservice that maintains a communication connection with the user terminal;

Parsing the call request to obtain designated data, where the designated data includes the ip address, request header, or request parameter of the user terminal;

Obtaining the gray-scale strategy provides a gray-scale strategy provided by the terminal, and the gray-scale strategy is a strategy that instructs at least two microservice clusters to perform gray-scale publishing;

Judging whether the specified data falls within the preset range of the one gray scale strategy;

If the specified data does not fall within the preset range of the integrated gray-scale strategy, use a preset gray-level strategy judgment method to determine whether the current microservice belongs to the integrated gray-scale strategy;

If the current microservice does not belong to the gray-scale integration strategy, determining whether the target microservice belongs to the gray-scale integration strategy;

If the target microservice belongs to the gray-scale policy, then the call request is diverted to the gray-scale service instance of the target microservice, and a signal connection channel is established, wherein one end of the signal connection channel is connected to the The other end of the user terminal is connected to gray-scale service instances of other micro-services in the same gray-scale strategy except for the target micro-service.
The computer-readable storage medium according to claim 18, wherein the specified data is a character string recorded in a pre-appointed position in the request header, the one gray scale strategy defines a plurality of preset ranges, and the judgment The step of whether the specified data falls within the preset range of the one gray scale strategy includes:

According to a preset similarity algorithm, calculate a similarity value between the designated data and a preset character string, and determine whether the similarity value is less than a preset similarity threshold;

If the similarity value is not less than the preset similarity threshold, then obtain the first version gray user, the second version gray user,..., the first version gray user corresponding to the nth version gray user agreed in the one gray policy. A keyword, a second keyword, ..., an nth keyword, in which the one grayscale strategy pre-appoints n versions of grayscale users;

Determine whether the designated data records the first keyword, the second keyword, ... or the nth keyword;

If the designated data records the first keyword, the second keyword, ... or the nth keyword, it is determined that the designated data falls within the preset range of the gray-scale strategy, and the user The terminal is recorded as a version gray user corresponding to the first keyword, the second keyword, ... or the nth keyword.
The computer-readable storage medium according to claim 19, wherein the similarity value between the designated data and the preset character string is calculated according to a preset similarity algorithm, and it is determined whether the similarity value is Steps that are less than the preset similarity threshold include:

Use the formula:

Calculate the similarity value between the specified data and the preset character string, where similarity is the similarity value, A is the character frequency vector of the specified data, B is the character frequency vector of the preset character string, and Ai is the character frequency vector of the specified data. The number of occurrences of the i-th character of the designated data, and Bi is the number of occurrences of the i-th character of the preset character string;

Obtaining the designated similarity threshold corresponding to the preset character string according to the correspondence between the character string and the similarity threshold;

It is determined whether the similarity value is less than the specified similarity threshold.